Comparer des méthodes

	Analyse Bayésienne de la Capabilité des Processus	Analyse de la Capabilité des Processus (Cp, Cpk)
Domaine	Plans d'expériences	Statistique
Famille	Process / pipeline	Process / pipeline
Année d'origine	Classical PCA: 1986; Bayesian extensions: 1990s–2000s	1986
Auteur d'origine	Bayesian extensions developed by multiple authors including Bernardo, Smith, and Vannman; classical PCA by Juran and Kane (1986)	Victor Kane
Type	Bayesian statistical quality method	Quantitative process evaluation index
Source fondatrice	Kotz, S., & Johnson, N. L. (2002). Process Capability Indices — A Review, 1992–2000. Journal of Quality Technology, 34(1), 2–19.	Kane, V. E. (1986). Process capability indices. Journal of Quality Technology, 18(1), 41–52.
Alias	Bayesian PCA, Bayesian capability indices, Bayesian Cp/Cpk estimation, Bayesian process performance analysis	Process Capability Indices, Capability Study, Süreç Yeterlilik Analizi, Process Performance Analysis
Apparentées	5	2
Résumé	Bayesian Process Capability Analysis integrates Bayesian inference with classical capability indices (Cp, Cpk, Cpm) to estimate how well a production process meets specification limits. Rather than relying solely on observed sample data, it incorporates prior knowledge about process parameters — yielding more stable and credible estimates of process capability, especially under small sample sizes common in manufacturing and quality engineering.	Process Capability Analysis quantifies how well a manufacturing or business process produces output within specified tolerance limits. Introduced formally by Victor Kane in 1986, it summarises process spread and centering into dimensionless indices — most notably Cp and Cpk — allowing engineers and quality managers to judge whether a stable process is inherently capable of meeting customer or design specifications consistently.